surging | service engine that provides a lightweight

by fanliang11 C# Version: 1.0.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(6)Vulnerabilities Install Support

kandi X-RAY | surging Summary

surging is a C# library typically used in Institutions, Learning, Administration, Public Services, Web Services, Kafka applications. surging has no vulnerabilities, it has a Permissive License and it has medium support. However surging has 101 bugs. You can download it from GitHub.

Surging is a micro-service engine that provides a lightweight, high-performance, modular RPC request pipeline. support Event-based Asynchronous Pattern and reactive programming ,The service engine supports http, TCP, WS,Grpc, Thrift,Mqtt, UDP, and DNS protocols. It uses ZooKeeper and Consul as a registry, and integrates it. Hash, random, polling, Fair Polling as a load balancing algorithm, built-in service governance to ensure reliable RPC communication, the engine contains Diagnostic, link tracking for protocol and middleware calls, and integration SkyWalking Distributed APM

Support

Quality

Security

License

Reuse

Support

surging has a medium active ecosystem.

It has 3189 star(s) with 930 fork(s). There are 306 watchers for this library.

It had no major release in the last 12 months.

There are 230 open issues and 117 have been closed. On average issues are closed in 107 days. There are 20 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of surging is 1.0.0

Quality

surging has 101 bugs (0 blocker, 0 critical, 55 major, 46 minor) and 42 code smells.

Security

surging has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

surging code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

surging is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

surging releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

surging saves you 10942 person hours of effort in developing the same functionality from scratch.

It has 22187 lines of code, 0 functions and 1124 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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surging Key Features

No Key Features are available at this moment for surging.

surging Examples and Code Snippets

No Code Snippets are available at this moment for surging.

Community Discussions

Trending Discussions on surging

Firestore read data count does not match documents queries count

clustering multiple categorical columns to make time series line plot in matplotlib

Any workaround to make moving average time series line plot in matplotlib?

How to retrieve data from a json

Node.js remove HTML with replace() and regex

removing stop words and string.punctuation

QUESTION

Firestore read data count does not match documents queries count

Asked 2020-Oct-14 at 13:05

I have encountered some issue when trying to figure out and calculate the firestore read count. The firestore read count is always surging up at a very high rate (100 counts increment every time I reload the page) even though there are only around 15 users documents. Even when I am not reloading the page, the firestore read count would go up itself, is this due to the subscribe behaviour that cause the read data action refreshing from time to time? (I have read some articles recommend to use "once" if user want to extract data just once).

Bellow is the code snippet (ts):

...

ANSWER

Answered 2020-Oct-14 at 13:05

The reads counts are focused on the number of documents retrieved.

Lets set these 4 scenarios:

A collection of 10 users, you run a collection("users").get() call: you will get back 10 employee documents, and be charged for 10 reads.
A collection of 10,000 users, you run a collection("users").get() call: you will get back 10,000 users, and be charged for 10,000 reads.
A collection of 10,000 employees, you run a collection("users").get().limit(10) call: you will get back 10 users, and be charged for 10 reads.
A collection of 10,000 users, 15 of which are named "Carl" and you run a collection("users").where("first_name", "==", "Carl") call, you will get back 4 users and be charged for 15 reads.

On the other hand, if you are listening to the whole collection users (no where() or .orderBy() clauses) and you have an active onSnapshot() listener then you will be charged for a document read operation each time a new document is added, changed, or deleted in the collection users.

You might want to take a look into your workflow to check whether other process are making changes on your collection when checking the read operations.

Finally, something to keep in mind is that the read ops in your report might not match with the billing and quota usage. There is a feature requests in the Public Issue Tracker realted to this inquiry - reads on Firestore: here. You can "star" it and set the notifications to get updates on them. Also, you can create a new one if necessary.

Source https://stackoverflow.com/questions/64205087

QUESTION

clustering multiple categorical columns to make time series line plot in matplotlib

Asked 2020-Sep-14 at 23:32

I am interested in how the COVID pandemic is affecting meat processing plants across the country. I retrieved NYT COVID data by county level and statistical data from the food agency. Here I am exploring how COVID cases are surging in counties where major food processing plants are located because more sick employees in plants might bring negative impacts to the business. In my first attempt, I figured out moving average time series plots where COVID new cases vs 7 days rolling mean along the date.

But, I think it would be more efficient I could replace the graph which represents num-emp and new-cases by counties in the for loop. To achieve this, I think it would be better to cluster them by company level and expand them into multiple graphs to prevent the lines from overlapping and becoming to difficult to see. I am not sure how to achieve this from my current attempt. Can anyone suggest a possible ways of doing this in matplotlib? Any idea?

my current attempt:

Here is the reproducible data in this gist that I used in my experiment:

import pandas as pd import matplotlib.pyplot as plt import matplotlib.dates as mdates import seaborn as sns from datetime import timedelta, datetime

...

ANSWER

Answered 2020-Sep-14 at 23:32

There were a couple of issues, I've made inline notations
The main issue was in the .groupby
- The data is already selected by 'country_state' so there's no need to groupby it
- Only reset_index(level=1), keep date in the index for rolling
- .unstack() was creating multi-level column names.
Set ci=None for plotting.
It doesn't make sense to use 'num-emp' as a metrics. It's constant across time.
- If you want to see the plot, swap 'cases' in the loop, for 'num-emp'.
I think the best way to see the impact of COVID on a given company, is to find a dataset with revenue.
Because food processing plants are considered critical infrastructure, there probably won't be much change in their head count, and anyone who is sick, is probably on sick leave vs. termination.

Source https://stackoverflow.com/questions/63851071

QUESTION

Any workaround to make moving average time series line plot in matplotlib?

Asked 2020-Sep-10 at 17:23

I want to understand how covid pandemic is affecting the supply chain industry such as meat processing plants. I retrieved NYT covid data by county level and statistical data from food agency, so I want to understand how covid cases are surging in counties where major food processing plants are located. To do so, I figured out the right data and able to make it ready for rendering a nice time series chart. However, I found issues of getting the right plotting data for that because the resulted plot is not getting the expected output. Here is what I tried so far:

my attempt:

Here is the final aggregated covid time series data that I am interested in this gist. Here is my current attempt:

...

ANSWER

Answered 2020-Sep-10 at 09:25

We have graphed the moving average of the number of outbreaks and new outbreaks for one state only. The process involved adding the moving average columns to the data frame extracted for a particular state and drawing a two-axis graph.

Source https://stackoverflow.com/questions/63822959

QUESTION

How to retrieve data from a json

Asked 2020-Jul-06 at 02:28

I retrieved a dataset from a news API in JSON format. I want to extract the news description from the JSON data.

This is my code:-

...

ANSWER

Answered 2020-Jul-05 at 20:08

There are few corrections needed in your code.. below code should work and i have removed API KEY in answer make sure that you add one before testing

Source https://stackoverflow.com/questions/62745497

QUESTION

Node.js remove HTML with replace() and regex

Asked 2018-Aug-21 at 11:58

Currently, I am writing some node.js code to remove all HTML in a string. This one of the string that I need to process:

...

ANSWER

Answered 2018-Aug-21 at 11:58

You need to add g to perform global matching

Source https://stackoverflow.com/questions/51948085

QUESTION

removing stop words and string.punctuation

Asked 2017-Aug-04 at 22:24

i can't figured out why this doesn't works:

...

ANSWER

Answered 2017-Aug-04 at 22:21

In this line change try changing 'or' to 'and' that way your list will return only words that are both not a stop word and are not punctuation.

Source https://stackoverflow.com/questions/45516207

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install surging

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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